Enter “write an article convincing CIOs why they should adopt generative AI” into ChatGPT’s prompt and this article could be it. Thankfully it isn’t, but it is this very ability to create compelling content within minutes that has captured the world’s attention in a snap.
Businesses are not shy to match the enthusiasm: 42% of companies surveyed in Accenture’s A New Era of Generative AI for Everyone report already want to make a large investment in ChatGPT this year. And despite current economic challenges, IDC reported AI spending (which includes generative AI) in Asia Pacific to nearly double from US$9.8 billion in 2023 to US$18.6 billion by 2026.
Going beyond creation: the enterprise case for generative AI
Given how we are in a time where businesses are required to do more with less, it’s no surprise why many are placing big bets on generative AI—especially as AI entered its language-mastery phase.
Earlier phases of AI have made their presence felt through deep analysis and predictive capabilities, but this is the first time AI can discern language complexities such as context and intent thanks to advances in large language models (LLMs) and foundation models. Now, AI can mimic human dialogue or decision-making in ways that feel distinctly human. One can only imagine its impact on human creativity and productivity.
There are enough headlines about its creation capabilities, but generative AI has more to offer businesses than just drafting emails or writing code; companies will use generative AI to reinvent the way work is done. After all, language tasks account for 62% of the total time employees work. In a recent video, Senthil Ramani, Senior Managing Director and Head of Applied Intelligence at Asia Pacific, Africa, Middle East, and LATAM, categorised the generative AI opportunities as the three Ps: productivity, programming, and personalisation.
When it comes to boosting productivity, generative AI goes beyond automating tasks. We anticipate it to act as an advisor and co-pilot for every worker, empowering them with the intelligence they need to elevate what they can achieve across functions, from human resource to competitive intelligence. In the example of customer support conversations, having a bot that understands a customer’s intent, formulates answers, and improves the accuracy and quality of answers removes manual intervention, enabling employees to channel their efforts toward more strategic initiatives.
Next up is programming. Generative AI is reinventing software engineering and creating the ability to do things better and faster. For developers, this means an invaluable hand in rapidly converting one programming language to another, automating code-writing, and mastering programming tools. The forward-thinking ones can even leverage generative AI to predict and pre-empt problems and manage system documentation.
It is also in this era of personalised experiences that generative AI can shine. Its sophisticated understanding of historical context, next best actions, summarisation capabilities, and predictive intelligence will spark new levels of hyper-efficiency and hyper-personalisation in the front and back office, reinventing business process automation as we know it.
And it is key to note these can be achieved securely. Generative AI is fully capable of supporting enterprise governance and information security, protecting against fraud, improving regulatory compliance, and proactively identifying risks.
Key considerations when getting started on generative AI
While we’re still in the early stages of the generative AI revolution, companies are already experimenting with off-the-shelf foundation models to get a leg up on the competition. But is it enough to consume generative AI and LLMs currently available in the market?
Likely not. Accenture’s A New Era of Generative AI for Everyone report posits how the biggest value will be derived when enterprises fine-tune these models with their own data, which can support specific downstream tasks across the entire business to elevate employee capabilities, delight customers, enable new business models, and boost business agility and resilience. In other words, going beyond plug-and-play models will be key to unlocking new performance frontiers.
As with all ground-breaking innovations that came before, treading the generative AI ground with caution is critical to ensure successful adoption and execution. We highlight three areas of consideration:
1. Navigating (and migrating) risks
With rapid AI adoption comes the need for robust, responsible AI compliance regimes in place to ensure AI reflects the broader business and societal norms of responsibility, fairness, and transparency. More importantly, business leaders themselves need to be aware of the potential issues around bias and discrimination, intellectual property, data privacy and security, product liability, and trust, because it is them who should define and lead responsible AI principles. This can then be translated into an effective governance structure for risk management and compliance across the business.
2. Understanding the technology required
Quantity and quality of data will underpin an AI’s system efficacy. Having a modern enterprise data platform with trusted and reusable data sets will significantly benefit generative AI’s learning. And in a time where ESG is in the spotlight, be aware if your enterprise has a sustainable technology foundation: one that provides the right technical infrastructure, architecture, operating model, and governance structure to meet high computing demands while keeping a close eye on sustainable energy consumption.
3. Enabling adoption at scale
Generative AI’s impact will be felt the most when deployed at every level and function. This can happen when business leaders reinvent the way work is done and lead the change in job redesign, task redesign, and employee reskilling. Since success with generative AI requires equal attention to people, training, and technology, investment in talent is needed to empower people on creating AI and using AI. Only then can they introduce a new dimension of human and AI collaboration and define new performance frontiers.
The advent of AI has the potential to transform work as we know it. Every job will be impacted, with most being transformed and many new ones being created. We’re right now at AI’s new inflection point, and like it or not, it will fundamentally transform everything, from science to business. It’s your choice to define the top quartile for your industry or simply be in it.